Or: Yet More Ways to Lie With Statistics.
Last Thursday, the month-over-month percent change in factory orders for February was announced at 1.8%. The expected number was 1.5%. Sounds like good news, right? Unfortunately, the January number was revised from -1.9% to -3.5% in the same release.
The easiest way to make a month-over-month change look better is to revise the prior month down.
Let's walk through with real numbers. Say the index level is 100 on December 31. On January 31, it has dropped 1.9% to 98.1. On February 28, the expectation is that it will have risen 1.5% to 99.6.
Instead, after the numbers came out last week, we learn that the following path was actually realized: 100 on December 31. On January 31, a 3.5% drop to 96.5. On February 28, a better than expected rise of 1.8% to 98.2.
So February's month-over-month change was better than expected, and yet because of the revision to the January numbers, we are 1.3% lower (98.2 vs 99.6) than the absolute expected level!
I've written before about the dangers of misinterpreting comparative statistics; this is an excellent tangible example.